Automation and Regulatory Compliance: How LILAB Optimized Financial Risk Management

Introduction

In an increasingly demanding financial environment, a major financial institution in Peru faced the challenge of adapting to stringent regulations for the prevention of money laundering and terrorist financing. With the rise in regulations imposed by the Superintendency of Banking, Insurance, and AFP (SBS) and the Financial Intelligence Unit (UIF-Perú), the client needed an advanced technological solution to manage risks efficiently and comply with regulations swiftly. The key was to automate critical processes and enhance the detection of suspicious activities in real time.

The Challenge

The client faced several challenges that compromised their ability to prevent money laundering:

Complex Regulatory Compliance: The institution had to constantly report to UIF-Perú and SBS, adhering to strict regulations.
Handling Large Volumes of Data: Reviewing transactional information, analyzing customer profiles, and evaluating high-risk geographical areas required continuous and exhaustive processes.
Lack of Automation: Manual processes limited the speed and accuracy of assessing suspicious transactions, affecting the ability to efficiently monitor high-risk customers.
LILAB's Solution

LILAB developed a customized anti-money laundering platform specifically designed to address the client’s needs. This comprehensive solution included several innovative modules that optimized financial risk management:

Configuration and Alerts Module: Automated the identification of suspicious behaviors through configurable alerts based on customizable risk variables.
Customer Assessment and Monitoring: Customers were segmented by risk levels (high, medium, and low), with a dynamic scoring system that updated automatically based on their transactions and behaviors.
Regulatory Reporting Automation: Automatic generation of reports tailored to the SBS and UIF-Perú requirements allowed for faster and more efficient regulatory compliance control.
Geographical Risk Management and Matrices: Implemented a system that assigned risk levels to specific geographical areas, facilitating detailed analysis and regional risk management.
Implementation Process

Initial Analysis: LILAB began with a thorough assessment of the client’s regulatory needs, current technological infrastructure, and areas of highest risk.
Custom Development: The solution was configured modularly, ensuring each component of the system was adaptable to the business’s specifics. The approach included risk variable management, report automation, and real-time customer scoring.
Phased Implementation: The platform was implemented gradually, allowing the client to become familiar with each module. This approach enabled seamless integration into daily operations.
Training and Continuous Support: LILAB provided intensive training to the client’s team to ensure optimal use of the platform. Additionally, continuous technical support was offered for adjustments and post-implementation optimizations.
Results and Benefits

Automated Regulatory Compliance: The client significantly reduced the time required for report preparation, resulting in a notable improvement in compliance with SBS and UIF regulations.
Increased Operational Efficiency: Automation of alerts and risk monitoring allowed for quicker and more effective responses to potential suspicious activities, significantly reducing the risk of regulatory sanctions.
Proactive Risk Management: Thanks to continuous customer and risk zone segmentation and monitoring, the client enhanced their ability to mitigate money laundering risks in real time.
Resource Optimization: By automating manual tasks, the institution was able to free up human resources, allowing them to focus on strategic analysis and data-driven decision-making.